util: Add script to plot DRAM low power sweep
This change adds a script to generate graphs from the stats file output by the configuration script low_power_sweep.py. The graphs show stacked bars for time spent and energy consumed wherein each component of the stacked bar represents a DRAM power state (Idle, Refresh, Active, Active Power-down, Precharge Power-down and Self-refresh). The script generates one plot per delay value. It also generates a pdf (--pdf option) in which the graphs are laid out such that you can easily compare how the increasing delay and other swept params affect the resulting energy. Change-Id: Id80b0947bfde27e11e5505b23a3adb30f793a43f Reviewed-by: Wendy Elsasser <wendy.elsasser@arm.com> Reviewed-on: https://gem5-review.googlesource.com/5727 Reviewed-by: Andreas Sandberg <andreas.sandberg@arm.com> Maintainer: Andreas Sandberg <andreas.sandberg@arm.com>
This commit is contained in:
Radhika Jagtap
committed by
Andreas Sandberg
Andreas Sandberg
parent
1695c9933b
commit
9b4e797cdd
193
util/plot_dram/dram_sweep_plot.py
Executable file
193
util/plot_dram/dram_sweep_plot.py
Executable file
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#!/usr/bin/env python2
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# Copyright (c) 2014 ARM Limited
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# All rights reserved
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#
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# The license below extends only to copyright in the software and shall
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# not be construed as granting a license to any other intellectual
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# property including but not limited to intellectual property relating
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# to a hardware implementation of the functionality of the software
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# licensed hereunder. You may use the software subject to the license
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# terms below provided that you ensure that this notice is replicated
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# unmodified and in its entirety in all distributions of the software,
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# modified or unmodified, in source code or in binary form.
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#
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# Redistribution and use in source and binary forms, with or without
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# modification, are permitted provided that the following conditions are
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# met: redistributions of source code must retain the above copyright
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# notice, this list of conditions and the following disclaimer;
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# redistributions in binary form must reproduce the above copyright
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# notice, this list of conditions and the following disclaimer in the
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# documentation and/or other materials provided with the distribution;
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# neither the name of the copyright holders nor the names of its
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# contributors may be used to endorse or promote products derived from
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# this software without specific prior written permission.
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#
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
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# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
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# OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
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# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
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# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
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# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
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# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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#
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# Authors: Andreas Hansson
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try:
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from mpl_toolkits.mplot3d import Axes3D
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from matplotlib import cm
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import matplotlib.pyplot as plt
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import numpy as np
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except ImportError:
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print "Failed to import matplotlib and numpy"
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exit(-1)
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import sys
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import re
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# Determine the parameters of the sweep from the simout output, and
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# then parse the stats and plot the 3D surface corresponding to the
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# different combinations of parallel banks, and stride size, as
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# generated by the config/dram/sweep.py script
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def main():
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if len(sys.argv) != 3:
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print "Usage: ", sys.argv[0], "-u|p|e <simout directory>"
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exit(-1)
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if len(sys.argv[1]) != 2 or sys.argv[1][0] != '-' or \
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not sys.argv[1][1] in "upe":
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print "Choose -u (utilisation), -p (total power), or -e " \
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"(power efficiency)"
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exit(-1)
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# Choose the appropriate mode, either utilisation, total power, or
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# efficiency
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mode = sys.argv[1][1]
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try:
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stats = open(sys.argv[2] + '/stats.txt', 'r')
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except IOError:
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print "Failed to open ", sys.argv[2] + '/stats.txt', " for reading"
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exit(-1)
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try:
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simout = open(sys.argv[2] + '/simout', 'r')
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except IOError:
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print "Failed to open ", sys.argv[2] + '/simout', " for reading"
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exit(-1)
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# Get the burst size, number of banks and the maximum stride from
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# the simulation output
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got_sweep = False
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for line in simout:
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match = re.match("DRAM sweep with "
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"burst: (\d+), banks: (\d+), max stride: (\d+)", line)
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if match:
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burst_size = int(match.groups(0)[0])
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banks = int(match.groups(0)[1])
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max_size = int(match.groups(0)[2])
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got_sweep = True
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simout.close()
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if not got_sweep:
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print "Failed to establish sweep details, ensure simout is up-to-date"
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exit(-1)
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# Now parse the stats
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peak_bw = []
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bus_util = []
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avg_pwr = []
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for line in stats:
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match = re.match(".*busUtil\s+(\d+\.\d+)\s+#.*", line)
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if match:
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bus_util.append(float(match.groups(0)[0]))
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match = re.match(".*peakBW\s+(\d+\.\d+)\s+#.*", line)
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if match:
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peak_bw.append(float(match.groups(0)[0]))
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match = re.match(".*averagePower\s+(\d+\.?\d*)\s+#.*", line)
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if match:
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avg_pwr.append(float(match.groups(0)[0]))
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stats.close()
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# Sanity check
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if not (len(peak_bw) == len(bus_util) and len(bus_util) == len(avg_pwr)):
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print "Peak bandwidth, bus utilisation, and average power do not match"
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exit(-1)
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# Collect the selected metric as our Z-axis, we do this in a 2D
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# grid corresponding to each iteration over the various stride
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# sizes.
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z = []
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zs = []
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i = 0
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for j in range(len(peak_bw)):
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if mode == 'u':
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z.append(bus_util[j])
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elif mode == 'p':
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z.append(avg_pwr[j])
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elif mode == 'e':
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# avg_pwr is in mW, peak_bw in MiByte/s, bus_util in percent
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z.append(avg_pwr[j] / (bus_util[j] / 100.0 * peak_bw[j] / 1000.0))
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else:
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print "Unexpected mode %s" % mode
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exit(-1)
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i += 1
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# If we have completed a sweep over the stride sizes,
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# start anew
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if i == max_size / burst_size:
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zs.append(z)
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z = []
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i = 0
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# We should have a 2D grid with as many columns as banks
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if len(zs) != banks:
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print "Unexpected number of data points in stats output"
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exit(-1)
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fig = plt.figure()
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ax = fig.gca(projection='3d')
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X = np.arange(burst_size, max_size + 1, burst_size)
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Y = np.arange(1, banks + 1, 1)
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X, Y = np.meshgrid(X, Y)
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# the values in the util are banks major, so we see groups for each
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# stride size in order
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Z = np.array(zs)
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surf = ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=cm.coolwarm,
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linewidth=0, antialiased=False)
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# Change the tick frequency to 64
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start, end = ax.get_xlim()
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ax.xaxis.set_ticks(np.arange(start, end + 1, 64))
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ax.set_xlabel('Bytes per activate')
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ax.set_ylabel('Banks')
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if mode == 'u':
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ax.set_zlabel('Utilisation (%)')
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elif mode == 'p':
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ax.set_zlabel('Power (mW)')
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elif mode == 'e':
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ax.set_zlabel('Power efficiency (mW / GByte / s)')
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# Add a colorbar
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fig.colorbar(surf, shrink=0.5, pad=.1, aspect=10)
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plt.show()
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if __name__ == "__main__":
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main()
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